Perceptually-based language to simplify sketch recognition user interface development

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 473-495).Diagrammatic sketching is a natural modality of human-computer interaction that can be used for a variety of tasks, for example, conceptual design. Sketch recognition systems are currently being developed for many domains. However, they require signal-processing expertise if they are to handle the intricacies of each domain, and they are time-consuming to build. Our goal is to enable user interface designers and domain experts who may not have expertise in sketch recognition to be able to build these sketch systems. We created and implemented a new framework (FLUID - f acilitating user interface development) in which developers can specify a domain description indicating how domain shapes are to be recognized, displayed, and edited. This description is then automatically transformed into a sketch recognition user interface for that domain. LADDER, a language using a perceptual vocabulary based on Gestalt principles, was developed to describe how to recognize, display, and edit domain shapes. A translator and a customizable recognition system (GUILD - a generator of user interfaces using ladder descriptions) are combined with a domain description to automatically create a domain specific recognition system.(cont.) With this new technology, by writing a domain description, developers are able to create a new sketch interface for a domain, greatly reducing the time and expertise for the task Continuing in pursuit of our goal to facilitate UI development, we noted that 1) human generated descriptions contained syntactic and conceptual errors, and that 2) it is more natural for a user to specify a shape by drawing it than by editing text. However, computer generated descriptions from a single drawn example are also flawed, as one cannot express all allowable variations in a single example. In response, we created a modification of the traditional model of active learning in which the system selectively generates its own near-miss examples and uses the human teacher as a source of labels. System generated near-misses offer a number of advantages. Human generated examples are tedious to create and may not expose problems in the current concept. It seems most effective for the near-miss examples to be generated by whichever learning participant (teacher or student) knows better where the deficiencies lie; this will allow the concepts to be more quickly and effectively refined.(cont.) When working in a closed domain such as this one, the computer learner knows exactly which conceptual uncertainties remain, and which hypotheses need to be tested and confirmed. The system uses these labeled examples to automatically build a LADDER shape description, using a modification of the version spaces algorithm that handles interrelated constraints, and which also has the ability to learn negative and disjunctive constraints.by Tracy Anne Hammond.Ph.D

Creating the Perception-based LADDER sketch recognition language

Sketch recognition is automated understanding of hand-drawn diagrams. Current sketch recognition systems exist for only a handful of domains, which contain on the order of 10--20 shapes. Our goal was to create a generalized method for recognition that could work for many domains, increasing the number of shapes that could be recognized in real-time, while maintaining a high accuracy. In an effort to effectively recognize shapes while allowing drawing freedom (both drawing-style freedom and perceptually-valid variations), we created the shape description language modeled after the way people naturally describe shapes to 1) create an intuitive and easy to understand description, providing transparency to the underlying recognition process, and 2) to improve recognition by providing recognition flexibility (drawing freedom) that is aligned with how humans perceive shapes. This paper describes the results of a study performed to see how users naturally describe shapes. A sample of 35 subjects described or drew approximately 16 shapes each. Results show a common vocabulary related to Gestalt grouping and singularities. Results also show that perception, similarity, and context play an important role in how people describe shapes. This study resulted in a language (LADDER) that allows shape recognizers for any domain to be automatically generated from a single hand-drawn example of each shape. Sketch systems for over 30 different domains have been automatically generated based on this language. The largest domain contained 923 distinct shapes, and achieved a recognition accuracy of 83% (and a top-3 accuracy of 87%) on a corpus of over 11,000 sketches, which recognizes almost two orders of magnitude more shapes than any other existing system.National Science Foundation (U.S.) (grant 0757557)National Science Foundation (U.S.) (grant 0943499

Recognizing Interspersed sketches quickly

Sketch recognition is the automated recognition of hand-drawn diagrams. When allowing users to sketch as they would naturally, users may draw shapes in an interspersed manner, starting a second shape before finishing the first. In order to provide freedom to draw interspersed shapes, an exponential combination of subshapes must be considered. Because of this, most sketch recognition systems either choose not to handle interspersing, or handle only a limited pre-defined amount of interspersing. Our goal is to eliminate such interspersing drawing constraints from the sketcher. This paper presents a high-level recognition algorithm that, while still exponential, allows for complete interspersing freedom, running in near real-time through early effective sub-tree pruning. At the core of the algorithm is an indexing technique that takes advantage of geometric sketch recognition techniques to index each shape for efficient access and fast pruning during recognition. We have stresstested our algorithm to show that the system recognizes shapes in less than a second even with over a hundred candidate subshapes on screen.National Science Foundation (U.S.) (IIS Creative IT Grant #0757557

Graph Creation, Visualisation and Transformation

We describe a tool to create, edit, visualise and compute with interaction nets - a form of graph rewriting systems. The editor, called GraphPaper, allows users to create and edit graphs and their transformation rules using an intuitive user interface. The editor uses the functionalities of the TULIP system, which gives us access to a wealth of visualisation algorithms. Interaction nets are not only a formalism for the specification of graphs, but also a rewrite-based computation model. We discuss graph rewriting strategies and a language to express them in order to perform strategic interaction net rewriting

Freeform User Interfaces for Graphical Computing

報告番号: 甲15222 ; 学位授与年月日: 2000-03-29 ; 学位の種別: 課程博士 ; 学位の種類: 博士(工学) ; 学位記番号: 博工第4717号 ; 研究科・専攻: 工学系研究科情報工学専

Appearance-design interfaces and tools for computer cinematography: Evaluation and application

We define appearance design as the creation and editing of scene content such as lighting and surface materials in computer graphics. The appearance design process takes a significant amount of time relative to other production tasks and poses difficult artistic challenges. Many user interfaces have been proposed to make appearance design faster, easier, and more expressive, but no formal validation of these interfaces had been published prior to our body of work. With a focus on novice users, we present a series of investigations into the strengths and weaknesses of various appearance design user interfaces. In particular, we develop an experimental methodology for the evaluation of representative user interface paradigms in the areas of lighting and material design. We conduct three user studies having subjects perform design tasks under controlled conditions. In these studies, we discover new insight into the effectiveness of each paradigm for novices measured by objective performance as well as subjective feedback. We also offer observations on common workflow and capabilities of novice users in these domains. We use the results of our lighting study to develop a new representation for artistic control of lighting, where light travels along nonlinear paths

Proceedings of the Graduate Student Symposium of the 7th International Conference on the Theory and Application of Diagrams, July 5 2012

Proceedings of the Graduate Student Symposium held at the 7th International Conference on the Theory and Application of Diagrams, ( Diagrams 2012 ), held at the University of Kent on July 5, 2012. Dr. Nathaniel Miller, professor of in the School of Mathematical Sciences at UNC, served on the symposium organizing committee